sagawa/PubChem-10m-deberta
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35
Datasets:
Multilinguality:
monolingual
Size Categories:
100K<n<1M
Language Creators:
expert-generated
Source Datasets:
original
License:
smiles
stringlengths 3
3.54k
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[NH3+]C1CC([NH+]2CCN(CC3CC3)CC2)C1 |
CC(=O)c1cccc(NS(=O)(=O)c2cccc(C(=O)[O-])c2C)c1 |
C[NH2+]Cc1cnoc1C1CCOC1 |
CC(CNC(=O)OC(C)(C)C)NOCc1ccccc1 |
N#CC(=NNc1ccccc1)c1nc(-c2ccc3ccccc3c2)c(N=Nc2ccccc2)s1 |
Cc1ccc(C(OCCOC(c2ccccc2)c2ccc(C)cc2)c2ccccc2)cc1 |
COc1cccc2c(C)cc(SCC#N)nc12 |
CC1(C)C(=O)Nc2cccc(CNc3nc(Nc4ccc(C5CC[NH+](C(C)(C)O)CC5)c5c4OCO5)ncc3Cl)c21 |
CC1CN(CC(=O)NC2CCCC2)c2ccccc2S1 |
CCNC(=[NH+]Cc1nccn1Cc1ccccc1)N1CCC(OCC2CCCCO2)CC1 |
CCOC(=O)CCCCN1CC[NH+](Cc2cc3nc(N4CCOC(c5cccc6[nH]ncc56)C4)ncc3s2)CC1 |
N#CSCC(=Cc1ccccc1)SC#N |
COC1OC(C)C(OCc2ccccc2)C(OCc2ccccc2)C1OC1OC(COC(C)=O)C(OC(C)=O)C(OC(C)=O)C1NC(=O)CCl |
C=CCN1C(=O)C(=Cc2ccc(OC(C)CC)c(OC)c2)C(=O)NC1=S |
CCCOc1nc(NN)nc(N(CC)C(C)C)n1 |
CC(C)c1ccc(NC(=O)C(=O)Nc2cc(C(F)(F)F)cc(C(F)(F)F)c2)cc1 |
Cc1ccc(NC(=O)c2ccc(C)c(NC(=O)C[NH+]3CCC(C(=O)N4CCCC4C(=O)Nc4cc(C(=O)NC5CCCCC5)ccc4Cl)CC3)c2)cc1F |
CCCCCC[NH+]1CCC(C(=O)CC)(c2cccc(O)c2)CC1 |
O=C(C1CCN(c2ccc(Cl)cc2)C1=O)N1CCC(c2nc3ccccc3s2)CC1 |
O=C1c2cc(N=Nc3c(O)c(C(=O)Nc4ccccc4)cc4ccccc34)ccc2-c2ccc(N=Nc3c(O)c(C(=O)Nc4ccccc4)cc4ccccc34)cc21 |
CC(C)c1nc(=O)cc(N2CC(C[NH3+])OC(C)(C)C2)[nH]1 |
COc1ccccc1CN1C(=O)C(Nc2ccccc2OC)=C(c2ccc(C)c(C)c2)C1=O |
O=C1NCC[NH+](Cc2cccc(OC3CCCC3)c2)C12CCCC2 |
CCCCn1c(SCC(=O)NCC(=O)NCC)nc2ccccc2c1=O |
Cn1cc(C(=O)N2CCCC2CO)nn1 |
C[NH+](C)Cc1ccc(S(=O)(=O)Nc2ccc3c(c2)nc(C(C)(C)C)n3CC2CCCCC2)cc1 |
CCN(CC)C(=O)CNc1nc(C(N)=O)ccc1N |
CCC(C(=O)[O-])[NH+]1CC(O)CCC1C |
CC(C)Oc1cncc(NCc2c(C(F)(F)F)cnn2C)n1 |
N#Cc1cc(NCc2cc(F)ccc2Br)ccc1[N+](=O)[O-] |
Clc1ccc(-c2nnc(NCc3ccco3)c3ccccc23)cc1 |
C[NH+](CC(=O)NC(C)(C)C)CC(=O)N1CCCCC1 |
CCCCC(C)=CC=C(C)[NH3+] |
CC(C)c1ncc(-n2ccc(C3CC3)n2)c(CCl)n1 |
Cc1cc(C)cc(NC(=O)CSC2=NC3(CC[NH+](C)CC3)N=C2c2ccc(F)cc2)c1 |
CCCCCCCCCCCOc1cscc1C(=O)OC |
Cc1ccccc1NC(=O)N(CCc1ccccc1)Cc1ccccn1 |
Oc1ccc(-c2cncc(C[NH+]3CC=C(c4ccccc4)CC3)c2)cc1 |
CC(=CCCC[NH3+])c1ccc(C2CCCCC2)cc1 |
CC(CO)([NH2+]CC(O)COc1cnsn1)c1ccccc1 |
[NH3+]CCCSCCCF |
CC(C)n1c(CNC(=O)c2ccc(Cl)cc2)n[nH]c1=S |
COCCOc1ccc(C(=O)[O-])c2ccccc12 |
CC(C)(C)[Si](C)(C)OC1CC(=O)C2C(c3ccccc3)=NOC12 |
O=C(NCCSc1ccccc1)c1cc2c(ccc3ccccc32)o1 |
CCc1nnc(SCc2cccc(C)c2)n1N=Cc1ccc(OC(C)(C)C)cc1 |
COc1c(C(C)=CC(=O)Nc2ccc(SC)cc2)cc2c(C)coc2c1C |
Cc1nc(C(=O)N2CCCC2(C)c2nc3c(C)cccc3n2C)c(-c2cccc(Cl)c2)s1 |
Cc1ncccc1NC(=O)c1nc2c(s1)CCCN2C(=O)C1CC1 |
CCn1ccc2ccc(C[NH2+]CC3(COC)CCC3)cc21 |
CC12Oc3ccc(Oc4ccnc5c4CCC(=O)N5)cc3C1C2NC(=O)c1ccc(C[NH+]2CCCC(O)C2)c(C(F)(F)F)c1 |
CC(C)(C)CC(=O)N(Cc1ccc(NC(=O)c2ccccc2)cc1)Cc1cccc(C[NH3+])c1 |
Cc1ccc(N(c2ccc(C)cc2)c2ccc(-c3ccc(CCC(=O)[O-])cc3)cc2)cc1 |
Cc1ccc(-c2cnc3c(C)cn(CC(=O)N(C)C)c3c2)s1 |
COc1ccc(C2Sc3cc(Cc4cccs4)ccc3N(CC[NH+](C)C)CC2OC(C)=O)cc1 |
Cc1ccccc1C(C(=O)NCCC(C)C)N(CC[NH+]1CCOCC1)C(=O)Cn1nnc2ccccc21 |
NNC(Cc1cccc(F)c1F)c1ccc(Br)cc1Br |
CCc1ccc(-c2csc(NC(=O)CSc3nnc(COc4cccc(C)c4)o3)n2)cc1 |
Cc1ccc(NC(=O)c2ccc(C)c(NC(=O)C(C)[NH+]3CCC(C(=O)NC(C(=O)Nc4ccc(NC(=O)c5ccccc5Cl)c(C)c4)C(C)C)CC3)c2)cc1F |
O=C(CN1C(=O)C(=O)N(Cc2ccccc2)C1=O)Nc1ccc(F)cc1F |
CC(C)N(C(=O)c1c(C=C(O[Si](C)(C)C)c2ccccc2)ccc2ccccc12)C(C)C |
COc1ccc(NC(=O)c2cc(-c3ccccc3F)on2)cc1S(=O)(=O)N1CCOCC1 |
CCCC1(c2ccccc2Cl)N=C(C[NH3+])OC(CC)C1=O |
CC[NH2+]C(Cc1sccc1Br)c1cc(C)ccc1OC |
Cc1cc(-c2c(C)nn(-c3nc(C#Cc4ccccc4)c(SC(C)C)s3)c2C(=O)[O-])cc(C)n1 |
CCCC[Sn](CCCC)(CCCC)c1cccc(COCOC)n1 |
CCOC(=O)c1ccc(-c2ccc3c(C(N)=O)c(NC(N)=O)[nH]c3c2)cc1 |
Cc1nn(C(C)C)c(N(C)C(C)(C)CO)c1N |
CC(C)COc1ccc(C2=C([NH+]3CCCC(CO)C3)C(=O)N(Cc3ccccc3)C2=O)cc1 |
CCCN(CC)c1ccc(N)s1 |
CCCCOc1ccc(-c2[nH]ncc2C(=O)NCc2ccc(OC)cc2OC)cc1 |
CSc1ccc(-c2ccc3c(c2)C(=O)N2CCN(C(=O)CCC(=O)[O-])CC2C(=O)N3)cc1 |
CCC1CCN(c2nc3cc(C)ccn3n2)C(C[NH3+])C1 |
CCCC[NH+](CC)CC(O)c1ccc(C)cc1 |
NC(=[NH2+])c1ccc(N2CCC(c3ccccc3)C2)nc1 |
CCOC(=O)c1cn[nH]c1S(=O)(=O)N(C)CC1CC1C |
Cc1ccc(S(=O)(=O)NCCCC[NH3+])cc1Br |
O=C(NCC1(c2ccccc2)CCC1)C1CCN(C(=O)c2ccco2)CC1 |
C#CCCCC[n+]1ccc(-c2ccncc2)cc1 |
O=C(Nc1ccc(SC(F)F)cc1)C1CC(=O)N(c2ccccc2)C1 |
Cc1ccccc1C(=O)NCCOc1cccc(NC(=O)OC(C)(C)C)c1 |
CNC(=O)C[NH+]1CCC(NC(NCC(C)Oc2ccccc2)=[NH+]C)CC1 |
CCCOc1ccc(C[NH+]2CCN(CC)CC2)cc1-c1nc(=O)c2cc3c(cc2[nH]1)ncn3Cc1ccccc1OC |
C(=Cc1ccc2cc(N3CCCc4ccccc43)ccc2c1)c1ccc2c(c1)C1(c3ccccc3-c3ccccc31)c1cc(N3CCCc4ccccc43)ccc1-2 |
Cc1occc1-c1nnc2sc(-c3ccccc3I)nn12 |
CCC(=O)Nc1ccc(-c2cc3c(o2)CCN(C(=O)c2ccc(C(F)(F)F)cc2)C3)cc1 |
CC[NH2+]C(c1ccc(C)cc1)C(C)CC |
Cc1cc(C)c2sc(N(Cc3ccco3)C(=O)c3ccc(SC(C)C)cc3)nc2c1 |
COC(=O)c1ccc(NC(C)Cn2ccnc2)c(F)c1F |
CN(Cc1ccccc1)C(=O)CCNc1ccccc1Cl |
Cc1oncc1C(=O)NCC=CC[NH3+] |
COc1cc(CC(=O)[O-])nc(OC(F)(F)F)c1C(F)F |
C#CCN(CCc1c[nH]c2[nH]c(N)nc(=O)c12)c1ccc(C(=O)NC(CCC(=O)NC(CCC(=O)NC(CCC(=O)[O-])C(=O)[O-])C(=O)[O-])C(=O)[O-])c(Cl)c1 |
CCN(C(=O)c1ccc(=O)n(Cc2cccc([N+](=O)[O-])c2)c1)c1ccccc1C |
CCNc1ncc(C2=NOC(C(=O)OCC)C2)cn1 |
CC=CC(=O)N(C)CCOc1ccc(Cl)cc1 |
CCC1NC(=O)CN(CC(C2CC2)C2CC2)C1=O |
Cc1ccc(C(=O)Nc2cc(NC(=O)CNC(=O)C3CC[NH+](C(C)C(=O)Nc4ccc(Cl)c(C(=O)NCC(C)C)c4)CC3)ccc2C)cc1 |
CSCC(C)[NH2+]Cc1nc(C)c(C)s1 |
O=C1CCC(C(=O)N2CCCN(C(=O)c3c[nH]c4ccccc34)CC2)=NN1 |
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dataset description
We downloaded PubChem-10m dataset from here and canonicalized it. We used the following function to canonicalize the data and removed some SMILES that cannot be read by RDKit.
from rdkit import Chem
def canonicalize(mol):
mol = Chem.MolToSmiles(Chem.MolFromSmiles(mol),True)
return mol
We randomly split the preprocessed data into train and validation. The ratio is 9 : 1.
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Size of downloaded dataset files:
263 MB
Size of the auto-converted Parquet files:
263 MB
Number of rows:
9,999,960